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Anomaly Detection for Road Traffic: A Visual Analytics Framework
IEEE Transactions on Intelligent Transportation Systems, 2017The analysis of large amounts of multidimensional road traffic data for anomaly detection is a complex task. Visual analytics can bridge the gap between computational and human approaches to detecting anomalous behavior in road traffic, making the data analysis process more transparent.
Maria Riveiro
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Road Anomaly Detection Using Smartphone: A Brief Analysis
Lecture Notes in Computer Science, 2019Identification of road anomaly not only helps drivers to reduce the risk, but also support for road maintenance. Arguably, with the popularity of smartphones including multiple sensors, many road anomaly detection systems using mobile phones have been proposed.
Eric Renault +2 more
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Testbed for the Experimental Evaluation of Road Anomaly Detection Algorithms
ICC 2022 - IEEE International Conference on Communications, 2022Eric Renault, Selma Boumerdassi
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A crowdsourcing-based road anomaly classification system
2016 18th Asia-Pacific Network Operations and Management Symposium (APNOMS), 2016Road networks are the most important facility to the public transportation in modern cities. Governments around the world allocate large amounts of budgets for the pavement maintenance every year. In this paper, we proposed a crowdsourcing solution to categorize road anomalies into safety related anomalies such as speed bumps and rumble strips, and ...
Ru-Yu Wang, Yi-Ta Chuang, Chih-Wei Yi
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Anomaly detection in driving behaviour by road profiling
2013 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 2013This paper presents a statistical method for detecting anomalous driving behavior by analyzing cross-sectional profiles of the road. A profile captures the way vehicles normally traverse the road; a statistical hypothesis test determines whether the observed behavior is anomalous.
Gabriel Agamennoni +3 more
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Inferring the Root Cause in Road Traffic Anomalies
2012 IEEE 12th International Conference on Data Mining, 2012We propose a novel two-step mining and optimization framework for inferring the root cause of anomalies that appear in road traffic data. We model road traffic as a time-dependent flow on a network formed by partitioning a city into regions bounded by major roads.
Sanjay Chawla, Yu Zheng 0004, Jiafeng Hu
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Image-Consistent Detection of Road Anomalies as Unpredictable Patches
2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 2023We propose a novel method for anomaly detection primarily aiming at autonomous driving. The design of the method, called DaCUP (Detection of anomalies as Consistent Unpredictable Patches), is based on two general properties of anomalous objects: an anomaly is (i) not from a class that could be modelled and (ii) it is not similar (in appearance) to non ...
Vojir, Tomas, Matas, Jiri
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Structural inpainting of road patches for anomaly detection
2015 14th IAPR International Conference on Machine Vision Applications (MVA), 2015Obstacle detection on the road is a key function for self-driving vehicles. A lot of research has focused on detecting large obstacles such as cars and pedestrians. Small obstacles can also be the source of serious accidents, especially at high speed. We present an approach for detecting anomalies on the road using a higher-order Boltzmann machine.
Asim Munawar, Clement Creusot
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Fuzzy Extensions of Isolation Forests for Road Anomaly Detection
2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2021In the presented paper the authors are showing the usage of fuzzy extensions of isolations forests for detecting road anomalies like potholes. Using the data acquired by the accelerometer in the smartphone and the proper smartphone application, the vibrations while driving over road were analyzed using multiple variants of extended isolation forests ...
Marcin Badurowicz +2 more
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Road Anomaly Classification for Low-Cost Road Maintenance and Route Quality Maps
2019 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops), 2019Traditional road maintenance methods are costly; requiring expensive equipment and manpower. Road quality categorization based on machine learning techniques, using real-time opportunistic data gathered from inexpensive open-source inertial systems, is a promising alternative.
Naufil Hassan +3 more
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